Anemia in Pregnancy: Urban–Rural Comparison of Management and Prevention Among Women of Child-Bearing Age in Anambra State,Nigeria

Abstract

We explored management and prevention practices concerning anemia in pregnancy (AIP) in Anambra State, Nigeria from a cross-sectional survey of 600 women of child-bearing age through a multistage random selection process. The objective is to identify factors that influence recognition and management of AIP. A knowledge index of 45 points was developed with the mean score of 5.9 points (5.9 ± 6.1 SD). Furthermore, 49.3% of the respondents had good knowledge. The urban respondents had good knowledge (66.7%) compared with their rural counterparts (32%). There were misconceptions on the causes, management, and prevention of AIP during pregnancy. Multiple regression analyses revealed that variables such as religious affiliation, education, and residence influenced the knowledge about AIP. A unit increase in the educational level of the women will bring about 0.644 units of increase in the knowledge of AIP (p = .003). A unit change from urban to rural locality would lead to 1.536 units increase in correct practices to prevent AIP (p < .001). A unit change to being married would lead to 0.936 unit increase in correct practices to prevent AIP (p = .025). Knowledge about the management and prevention of AIP was poor. Anemia-related education to improve knowledge and practice should be provided during antenatal care. Living in an urban community was associated with the odds ratio of 4.3 (95% CI [3.07, 6.07]) and 7.42 (95% CI [2.0, 27.6]) for knowledge and prevention of AIP, respectively.

Keywords

anemia pregnancy anemia in pregnancy knowledge communities Anambra State Nigeria

Introduction

Maternal mortality ratio (MMR) remains high in Nigeria despite the substantial reduction achieved in the maternal deaths globally. There has been a sustained effort to achieve a 75% reduction in MMR by 2015 compared with 2000,¹ and progress is made toward attaining the pending global developmental goals² as we pursued the sustainables, including significant reduction in MMR, despite global increase in general population, specifically among women of child-bearing age. MMR decreased from 380 to 210 per 100,000 live births between 1990 and 2014. This translates into a 45% reduction in MMR.

This global progress notwithstanding sub-Saharan Africa recorded a substantial increase in the maternal deaths for the period under review.³ Maternal mortality in Africa is still 14 times higher than that in the developed regions of the world. In Nigeria, for instance, MMR increased from 545 to 575 deaths per 100,000 live births between 2008 and 2013,^4,5 reflecting a worsening situation and failure in achieving fifth target of the global developmental goals.^4,6 Interventions were designed to reduce maternal mortality and achieve the target of 250 or less deaths per 100,000 live births in Nigeria. Maternal health continues to worsen, despite global and national investments in promoting improved access to quality maternal health services.⁶

The Millennium Development Goal-5 aimed to achieve a reduction in MMR to 125 per 100,000 live births by 2010 and to 75 by 2015 in Nigeria. The Sustainable Development Goal 3.1 targets reduction in MMR to less than 70 per 100 000 live births by 2030. However, the Nigerian Demographic and Health Survey showed that by 2008 and 2013, the MMR was 545 and 575 per 100,000 live births, respectively.^1,4,5 Anemia has been implicated as a major driver of the unwholesome MMR in Nigeria and other developing countries.⁷ According to Dim and Onah, a hospital study in Southeastern Nigeria reveals that 40.4% of women registered with the antenatal unit were anemic (hemoglobin [Hb] < 11.0 g/dL)⁸ This could be an underestimation of the true prevalence of anemia in pregnancy (AIP), given that most women deliver outside the health facilities in Nigeria.⁹

A key component of safe motherhood is the eradication of AIP. The World Health Organization (WHO) has produced estimates of the global burden of deaths attributable to anemia (all forms) in women of reproductive age.^8,10 Unfortunately, statistics on the prevalence of anemia are appalling, especially in resource-poor regions in the world. The WHO¹¹ estimates that two billion people—more than 30% of the world’s population—are anemic, although the prevalence rates vary because of the differences in socioeconomic conditions, lifestyles, food habits, and rates of communicable and noncommunicable diseases. In 2001, it was estimated that approximately 50% of all pregnant women suffer from anemia, globally with 52% of this in low-resource countries and 23% in high-resource regions.¹² The WHO estimates that more than half of the pregnant women in the world have a hemoglobin level indicative of anemia (<11.0 g/dL). The prevalence may, however, be as high as 56% or 61% in developing countries.¹³ WHO noted that in the developing countries, every second pregnant woman and about 40% of preschool children are anemic.¹¹

Iron deficiency is the most prevalent cause of anemia, but according to Gangopadhyay et al., only rarely does iron deficiency exist by itself.^14,15 Individuals who are deficient in iron are also deficient in other important micronutrients, although this association is often ignored by the public at large. Most of the deaths and problems associated with AIP could be prevented with attainable resources and skills.¹⁶ Unfortunately, Nigeria currently reports some of the lowest uptake of evidence-based interventions for improving maternal health in the world, for reasons linked to weaken the health service. All the same, while the phenomenon of AIP constitutes a universal social and public health category, its categorical imperatives and people’s knowledge, attitude, and practice toward it differ widely not only between societies but within societies, according to situation and social location.

This article presents the results of a study to explore the management and prevention of AIP among women of child-bearing ages as well as to interrogate the drivers of their practices. The main aim is to identify the key factors that influence to improve the management and prevention of AIP.

Methods

Study Area

Anambra State is located in the southeast geopolitical zone of Nigeria. The state lies on the eastern plains of the River Niger and covers an area of 4,416 square kilometers. The vegetation is typically semitropical rainforest, with humid climate and a mean temperature of about 870 F with the annual rainfall of 152 cm to 203 cm.

It shares a common border with Enugu and Kogi States to the north, Imo State to the east, and Delta State to the southwest. It has an estimated population of 4,418,032 in 2013 with an annual growth rate of 2.8%, projected to 5,073,868 in 2016. Anambra State is made up of 21 local government areas (LGAs) which are further divided into 330 political wards and approximately 1,394 communities. There are estimated 717,663 households and 456 health facilities including 21 general hospitals, 232 primary health care (PHC) centers, 189 health posts, 11 comprehensive health centers, 3 cottage hospitals, and 2 teaching hospitals. Patent medicine vendors (PMVs) scattered in both urban and rural communities also provide health options in Anambra State.

The study was limited to Onitsha South and Idemili South, representing urban and rural LGAs, respectively. The 2006 Nigeria population and housing census put the population of these LGAs at 136,662 and 207,683, respectively. Fegge town, in Onitsha South LGA, is an urban community with people from different walks of life and heterogeneous and high population density (density: 13,719.1/km²). On the other hand, Idemili South LGA consists of seven communities, namely, Akwu-Ukwu, Alor, Awka-Etiti, Nnobi, Nnokwa, Oba, and Ojoto. These are largely rural communities. Each community has one PHC center, while the LGA has only one general hospital in Nnobi.

Urban and rural LGAs were selected to ensure comparative analysis intended in this study. The major source of income for the people in the urban area is commerce and civil service, while agriculture is the major source of income for the rural LGA. Those in the rural LGA produce cassava, yam, palm wine, and raffia. Apart from farming, people in Idemili South engage in some trading, with very few in white-collar jobs. However, most of the residents of these communities are poor and this negatively affects their state of health.

Study Design

This is a comparative cross-sectional study, which was designed to obtain the factors that affect the prevention and management of AIP from a sample comprising women of child-bearing ages in rural and urban communities in Anambra State. It employs a structured other-administered interview schedule.

Study Population

The population for this study consisted of all mothers of child-bearing age (15–49 years) in the LGA. This constituted 22% of the total population.² Thus, the study population for the LGAs was estimated as 26,343 and 17,205 women of child-bearing age in Onitsha South and Idemili South, respectively, in 2013. Given the fertility of about 5.7 per woman and the population of women of child-bearing age, it was estimated that 10,887 women would be pregnant within the two study LGAs within a year and this constituted the target population for this study.

Inclusion Criteria

The criteria for inclusion in the study are woman who had delivered a baby within 6 months before the survey and woman has to be the resident within the study communities and not just visiting within the study period.

Sample Size

Using a 40.4% rate of occurrence of AIP in Southeastern Nigeria and a confidence interval of 95% with an estimated 4% level of precision, a sample size of 300 respondents was computed for the comparative study on urban and rural communities. This was doubled to cater for cluster effects in the sampling to get 600 respondents.

Sampling Procedure

A variant of the multistage sampling technique, which entails successive selection of community clusters or villages, streets, housing units, and respondents, was employed in each community to suit its local conditions. The LGAs in Anambra State were put into two clusters of urban and rural using the government gazette. One LGA was randomly selected from each cluster of LGAs. Subsequently, the sampling of communities, villages, and individuals followed.

First, in Idemili South, for instance, Ojoto community, which is the LGA Headquarters, was excluded to avoid the urban characteristics. Second, Alor community was randomly selected from the list of the remaining six communities, namely, Akwaukwu, Alor, Awka-Etiti, Nnobi, Nnokwa, and Oba. Third, two villages were randomly selected to form the sampling clusters from which eligible respondents, who had delivered within 6 months preceding the survey, were drawn.

The fourth stage was the selection of a starting point. A central location in each of the randomly selected communities was identified to serve as the starting point for data collection in the selected community. Two data collectors were assigned to cover each community cluster. The interviewers moved in opposite directions from the identified starting point in each cluster. Interviewers continued to turn right at any junction until the desired number of respondents is attained.

The sampling techniques were modified to suit the urban conditions. Fegge was purposively selected being the only community in which the streets formed the clusters.

Instrument for Data Collection

A structured interview schedule (other-administered questionnaire) was employed for the data collection in this study. The authors designed the instrument for this study and pretested in a postgraduate seminar of the Department of Sociology/Anthropology, University of Nigeria, Nsukka. Prior to this, the instrument was pretested in Nsukka urban community and Ibagwa Aka rural community for reliability and validity. The questionnaire covered information on the sociodemographic characteristics of the respondents as well as their child-bearing experiences. It also provided data on the women’s experiences with the PHC as well as their knowledge, attitude, and practice on AIP.

The instrument was carefully administered by the selected field assistants who were trained on the objectives and methods of the study. They visited the selected women in their homes and administered the interview.

Methods of Data Analysis

The data were carefully prepared by the data template with check program using Epi Info version 6.04 and transferred to SPSS version 19 for the actual analysis. Simple descriptive statistics were employed in characterizing the data. Bivariate correlation analyses were done using chi-square test, to illustrate the relationship or association between certain sociodemographic variables and knowledge, attitude, and practice on AIP as well as to test the study hypotheses. Furthermore, binary logistic regression was conducted using independent variables that correlated significantly with the dependent variable. The cut-off level of significance was p < .05.

Ethical Considerations

Ethical approval was obtained from the Health Research Ethics committee of the Nnamdi Azikiwe Teaching Hospital. Informed consent of the respondents was sought and received before interview commenced.

Results

Women were aged between 25 and 45 years with a mean age of 33.24 years (33.24 ± 5.23 SD). Ninety-one percent of the women were married. Furthermore, 94.2% attended school and 40.7% had tertiary education. More than three quarters (87%) were engaged in paid employment in the form of trading, teaching, civil service, and farming, among others. The respondents were predominantly Christians (Roman Catholics and others).

Although a majority (90.8%) of the respondents were not pregnant at the time of the study, they have all been pregnant at one point or the other as attested to by their child-bearing status. The respondents had between one to more than five pregnancies with a mean pregnancy of 3.77 (3.77 ± 1.79 SD). A majority (35.8%) had five or more pregnancies. Others (29.2% and 35%) had less than 3 and 3 to 4 pregnancies. With respect to the number of children that the respondents had at the time of the study, they had between less than three and more than five children. More than a third (36.5%) had five or more children, while a third (33.8%) had three to four children. Less than a third (29.7%) had less than three children.

The respondents’ knowledge of AIP was examined. Less than half (49.5%) of those interviewed indicated the awareness of AIP. There was a significant difference between the urban (67.0%) and rural (32.0%) respondents on the awareness of AIP (p < .001). To assess the knowledge of the respondents on AIP, an index of knowledge of anemia was developed with seven questions containing 45 items in the questionnaire. The questions sought to know if the respondents are aware of AIP and the causes, effects, symptoms, and management of AIP. The index gave a maximum of 45 points. However, the actual scores of the respondents ranged from 0 to 15 points with a mean score of 5.9 points (5.9 ± 6.1 SD). This was categorized as low if knowledge score is 0 to 5 and medium if knowledge is 6 to 10, while high knowledge is reflected as a knowledge score of 11 and above.

More than half (50.7%) of the respondents had low knowledge of AIP, while 4.3% and 45% had medium and high knowledge of AIP. The study compared the respondents between urban and rural communities. However, other variables were also considered, and results were compared on the basis of these. A third (33.3%) of the urban respondents had low score on the knowledge of AIP compared with their rural counterparts with 68.0% scoring low on the knowledge of AIP. None of the rural respondents made a medium score on the knowledge of AIP, while 8.7% of the urban respondents scored medium here. More than half (58.0%) of the urban respondents had high score on the knowledge of AIP. This compares favorably with their rural counterparts (32.0%) scoring high on the knowledge of AIP. The difference between the urban and rural respondents was statistically significant (χ² = 84.112; p < .001).

The striking finding here, however, is the low recognition of blood-building abilities as a factor in the incidence of AIP. This received very low mention both among the urban and rural respondents. There is a common belief among some women that anemia is caused by exposure to evil forces. A few blamed it on eating foreign foods and not foods eaten by the older generations during pregnancy. They stressed that they are traditional foods meant for women during pregnancy.

Furthermore, logistic regression analyses were conducted on the data to examine the factors that influence the knowledge and management of anemia in the communities. The dependent variables include knowledge of AIP, perception of causes of AIP, and practices to prevent AIP. The independent variables include the sociodemographic variables of the respondents. Other independent variables include both the cognitive and perceptual factors in the study.

First, the effect of urbanization of respondents on the knowledge of AIP was considered in a multinomial logistic regression analysis. Urbanization is often considered a nexus of the phenomenon of awareness, exposition, and knowledge. It was thus considered while controlling for other independent variables, namely, Catholicism, education, marital status, and age. The justification of the inclusion of these variables in the regression model is based on the realization that the Catholic urban woman is likely to respond to pregnancy health differently from the non-Catholic woman. Similarly, a woman with tertiary education may respond to pregnancy health in a different way from the lowly educated urban woman.

The consideration of these variables in the model is as follows:

Knowledge of AIP: This is the dependent variable measured in categorical scale, where 1 stands for good knowledge and 0 stands for poor knowledge.

Table 1 which revealed that some variables, namely, religious affiliation of the women, their high level of educational attainment, and residence are significantly related to their knowledge of AIP. It showed that living in urban communities increases chances of having good knowledge of AIP. Living in an urban community was associated with an odds ratio of 4.3 (95% CI [3.1, 6.7]) knowledge of AIP. It shows that there is a direct relationship between education and knowledge of awareness in pregnancy. In other words, the higher the level of education of the women, the higher their knowledge of AIP. It also shows that a unit increase in the educational level of the women will bring about 0.644 units of increase in the knowledge of AIP (p = .003). On the other hand, the younger urban women have better knowledge of AIP. On the other hand, age of the women is inversely related with the knowledge of AIP. A unit increase in the age of the women led to 0.361 unit reduction in knowledge about AIP among the respondents. However, this observation is not statistically significant (p = .057). Other variables with significant association with the knowledge of AIP in the regression model were location and religion.

Table 1.

Logistic Regression of Sociodemographic Characteristics of Respondents on Awareness and Knowledge of AIP.

Knowledge of AIP	OR [95% CI]	B	SE	Wald	df	Significance	[95% CI]
Knowledge of AIP	OR [95% CI]	B	SE	Wald	df	Significance	Lower	Upper
Location (urban = 1; rural = 0)	4.314 [3.066, 6.072]	1.256	.211	35.514	1	<.001	2.324	5.311
Education level (tertiary =1; <tertiary = 0)	3.234 [2.299, 4.549]	.644	.215	8.981	1	.003	1.249	2.899
Religion (Catholics = 1; others = 0)	0.462 [0.327, 0.654]	−.811	.194	17.550	1	<.001	0.304	0.649
Older women (≥34 years =1; <34 years = 0)	0.741 [0.534, 1.028]	−.361	.189	3.634	1	.057	0.481	1.010
Marital status (married = 1; not married = 0)	1.061 [0.606, 1.857]	.426	.313	1.855	1	.173	0.829	2.829

Abbreviation: AIP, anemia in pregnancy.

Another dependent variable employed in the logistic regression model was the respondents’ practices to prevent AIP. Table 2 revealed that only two variables, location of the respondents and their marital statuses, affect their practices to prevent anemia during the last pregnancy. Living in urban community was associated with an odds ratio of 7.4 (95% CI [2.0, 27.6]). The result showed that a unit change from urban to rural locality would lead to 1.536 units increase in correct practices to prevent AIP (p < .001). Similarly, being married influences correct practices taken to prevent AIP. A change to being married would lead to 0.936 unit increase in correct practices to prevent AIP (p = .025).

Table 2.

Logistic Regression of Sociodemographic Characteristics of Respondents on Practices to Prevent Anemia During the Last Pregnancy.

Practices to prevent anemia in the last pregnancy	OR [95% CI]	B	SE	Wald	df	Significance	[95% CI]
Practices to prevent anemia in the last pregnancy	OR [95% CI]	B	SE	Wald	df	Significance	Lower	Upper
Location (urban = 1; rural = 0)	7.416 [1.992, 27.600]	−1.536	.227	45.959	1	<.001	.139	.338
Education level (tertiary = 1; <tertiary = 0)	7.028 [1.530, 32.280]	−.050	.237	.044	1	.834	.613	1.551
Religion (Catholics = 1; others = 0)	17.948 [2.302, 139.921]	.111	.198	.317	1	.573	.772	1.675
Older women (≥34 years = 1; <34 years = 0)	0.094 [0.020, 0.434]	−.291	.193	2.262	1	.133	.503	1.073
Marital status (married = 1; not married = 0)	0.000	.936	.417	5.049	1	.025	1.147	5.867

Finally, the analysis was done to regress the sociodemographic, cognitive, and perceptual characteristics of the respondents on the practices to prevent AIP. The results are summarized in Table 3.

Table 3.

Logistic Regression of Sociodemographic Characteristics of Cognitive and Perceptual Factors Among Respondents on Practice to Prevent Anemia During the Last Pregnancy.

Practice to prevent anemia during last pregnancy	OR [95% CI]	B	SE	Wald	df	Significance	[95% CI]
Practice to prevent anemia during last pregnancy	OR [95% CI]	B	SE	Wald	df	Significance	Lower	Upper
Location (urban = 1; rural = 0)	7.416 [1.992, 27.600]	−2.443	.462	27.993	1	.000	.127	.454
Education level (tertiary = 1; <tertiary = 0)	7.028 [1.530, 32.280]	−.319	.252	1.602	1	.206	.426	1.150
Religion (Catholics = 1; others = 0)	17.948 [2.302, 139.9210]	.416	.217	3.676	1	.055	1.163	2.823
Older women (≥34 years = 1; <34 years = 0)	0.094 [0.020, 0.434]	−.203	.204	.998	1	.318	.524	1.169
Marital status (married = 1; not married = 0)	0.000	.727	.416	3.052	1	.081	.900	4.507
Knowledge of AIP (≥5.00 = 1; <5.00 =0)	0.000	1.910	.451	17.948	1	.000	.703	3.433
Perceptions of causes of AIP (≥1.00 = 1; <1 = 0)	0.124 [0.033, 0.462]	−.319	.532	.360	1	.549	1.336	2.896

Abbreviation: AIP, anemia in pregnancy.

The results are presented in Table 3, and it revealed that in addition to location, the knowledge of AIP influenced practices taken to prevent anemia during the last pregnancy among the respondents. Other variables in the model did not give any significant contribution to change in the practices taken to prevent AIP. All the same, the model contributed significant change in practice to prevent AIP (p = .19).

Discussion

This study looked at what pregnant women in rural and urban communities of Anambra State knew about serious illnesses that can occur during pregnancy. Most of these women mentioned illnesses that were related to malaria, such as convulsions, high fever, loss of consciousness, difficulty in breathing, severe weakness, and severe abdominal pain, but the bleeding received 87.5% mentions among the respondents. Most of these respondents saw bleeding during pregnancy as a very serious problem because it might be an indicator of a miscarriage taking place. All the same, many also highlighted high fever and severe weakness as major challenges during pregnancy. This agrees with the qualitative study carried out by Agomo et al.,¹⁷ which indicated that several pregnant women perceived high fever and general weakness as a normal sign of pregnancy.

Less than half of the respondents knew about AIP and also knew the causes of AIP. Previous studies have shown that Nigerian women have poor knowledge of AIP,^8,13 and similar results were observed in this study. Similar studies in Tanzania, Malawi, among others, have identified specific causes of AIP but in doing so identified very low knowledge among the respondents, particularly those in low socioeconomic class.^17,18 However, studies have not been systematically conducted in Nigeria to isolate the critical demographic and perceptual factors that act as intermediate variables in fostering the low level of knowledge or how knowledge affects knowledge and practices on AIP.

With regard to the practices, good knowledge of anemia has been acknowledged to have positive influence on practices to prevent or manage anemia. Previous studies have highlighted the effect of ignorance on health behaviors and health outcomes. For instance, the use of malaria interventions in the prevention of malaria during pregnancy have been found to be heavily dependent both on the level of awareness often associated with urbanism and educational status of the women in Nigeria.^15,20 Furthermore, the logistic regression results in this study confirmed the results discussed earlier. Practices to prevent or manage AIP are driven by general health concepts and knowledge, rather than from specific understanding of its importance.

The logistic regression shows that locality more than any other variable influence the knowledge and management of AIP in the study area. For instance, with respect to the contribution of each sociodemographic variable in the regression model, Table 1 shows that living in an urban area is associated with an odds ratio of 7.4 (95% CI [2.0, 27.6]) which is significant at <.001 level. Although religion showed a higher odds ratio of 17.95 (95% CI [2.3, 139.9]), the difference associated with the different religions was not significant. This leaves the urban factor as the most important element of the knowledge and management of AIP in the study area. Education followed this with an odds ratio of 7.0 (95% CI [1.5, 32.3]). This agrees with the findings of Okeibunor in a study looking at the use of community-directed interventions for health-care provisioning in Nigeria.¹⁹ Another study by Onyeneho et al. looked at the compliance with intermittent presumptive treatment and the use of insecticides-treated bed nets during pregnancy in Enugu State. Both studies found that both urbanism and education were the strongest factors that influenced the knowledge and management of common public health problems in the country.

The major limitation of this study, however, is that the focus is on only one state in Nigeria. This limits the varying experiences that could be associated with different health systems and environmental realities. However, the use of urban and rural localities undoubtedly provided some mirroring of differences that could occur if communities with varying sociodemographic realities including different health systems are included in the study. Be that as it may, the generalization of these results to wider settings is taken with caution. The merit of the study, however, is that it provides basis to larger studies that may look at states with different levels of health system performance and existential realities.

Conclusions

In conclusion, the study showed that though the people demonstrated awareness for anemia during pregnancy, this was not matched by the knowledge of management and prevention. Knowledge of management and prevention of AIP was poor. Anemia-related education should be provided during antenatal care (ANC). More important is the fact that the findings here confirm the arguments in the health belief model, and one can conclude that pregnant women in Anambra State would adopt anemia preventive measures if these measures were available and if they are sufficiently educated on the values of these measures.

However, the health workers who should educate and encourage the women to make optimal use of the focused ANC services are themselves short of the world expected standard. The health workers also need to be trained on appropriate communication skills that will ensure them to play their roles as facilitators on the use of focused ANC services positioned to control anemia during pregnancy. It is thus recommended that stakeholders ensure health education to promote effective access to the AIP control services among pregnant women as well as target health workers to create friendlier environment for the clients.

With respect to policy implications, this study shows that beyond the pregnancy-related pathways to anemia, there are other pathways such as the locality, environment, and education. All of these must be considered for an effective intervention in the management of AIP. A comprehensive perspective will provide holistic interventions to control AIP in both rural as well as in urban communities.

Footnotes

Acknowledgments

The authors thank the technical and scientific support of the Post Graduate Board of the Department of Sociology/Anthropology for the design and execution of this study.

Authors’ Contribution

N. G. O. contributed substantially to the conception and design of the study as well as analysis and interpretations of data. She drafted the manuscript and revised it critically for important intellectual content. She gave approval for this version of the manuscript to be published and agreed to be accountable to all aspects of the work in ensuring that questions related to the accuracy and integrity of any part of the work are appropriately investigated and resolved. O. U. I. contributed to design of the study, collection of data, and analysis and interpretations of data. She gave approval for this version of the manuscript to be published and agreed to be accountable to all aspects of the work in ensuring that questions related to the accuracy and integrity of any part of the work are appropriately investigated and resolved.

Supplemental Material

Supplemental material for this article is available online.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval and Consent to Participate

The Nnamdi Azikiwe University Teaching Hospital Health Research Ethics Committee gave ethical approval for the study. This was registered under number NAUTH/CS/66/VOL.7/15. Consent was sought and received from participants to participate in the study.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Obianuju U. Igweonu is a lecturer II in the social sciences unit of the school of general studies in the University of Nigeria, Nsukka. She is also undergoing her PhD program in the Department of Sociology/Anthropology, University of Nigeria. Her research interest is on maternal and adolescent health. As a young and upcoming academic, she has published a few papers in internationally recognized journals one of which is the Journal of Health, Population and Nutrition.

Nkechi G. Onyeneho is an associate professor of Health Sociology/Anthropology in the University of Nigeria, Nsukka. She is a current Takemi fellow for International Health in the Department of Global Health, Harvard School of Public Health, Harvard University. Her research interests include women's health and development. She is also interested in the health of the vulnerable groups including the elderly and young people in society. She has conducted researches on malaria, anaemia and neglected tropical diseases. Most of her researches are funded by local and international multi-lateral organizations like WHO, UNICEF, USAID, JMA among others. She has more than 40 publications to her credit despite her less than 15 years in academics.

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